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Knowledge extraction from a large on-line survey: a case study for a higher education corporate marketing

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For a higher education public institution, young in relative terms, featuring local competition with another private and both long-established and reputed one, it is of great importance to become a reference university institution to be better known and felt with identification in the society it belongs to and ultimately to reach a good position within the European Higher Education Area. These considerations have made the university governors setting up the objective of achieving an adequate management of the university institutional brand focused on its logo and on image promotion, leading to the establishment of a university shop as it is considered a highly adequate instrument for such promotion. In this context, an on-line survey is launched on three different kinds of members of the institution, resulting in a large data sample. Different kinds of variables are analysed through appropriate exploratory multivariate techniques (symmetrical methods) and regression-related techniques (non-symmetrical methods). An advocacy for such combination is given as a conclusion. The application of statistical techniques of data and text mining provides us with empirical insights about the institution members’ perceptions and helps us to extract some facts valuable to establish policies that would improve the corporate identity and the success of the corporate shop.
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Keywords: PLS path modelling; clustering; correspondence analysis; data and text mining; knowledge extraction; logit models; principal component analysis

Document Type: Research Article

Affiliations: 1: Departamento de Economía Aplicada III,University of the Basque Country (UPV/EHU), Bilbao, Spain 2: Departamento de Economía Aplicada,University of Burgos (UBU), Burgos, Spain

Publication date: November 1, 2011

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